def label_fusion(target_path, atlas_img_path_list, atlas_lab_path_list, out_file, probabilities, params_list):
out_dir = os.path.dirname(out_file)
out_name = os.path.basename(out_file).split(os.extsep, 1)[0]
if params_list[0] == 'Joint':
jointfusion_path = os.path.join(os.environ['ANTSPATH'], 'jointfusion')
prob_dir = os.path.join(out_dir, out_name)
prob_path = os.path.join(prob_dir, 'prob%d.nii.gz')
cmdline = [jointfusion_path, '3', '1']
cmdline += ['-g'] + atlas_img_path_list
cmdline += ['-tg', target_path]
cmdline += ['-l'] + atlas_lab_path_list
cmdline += ['-m', 'Joint']
cmdline += [item for sublist in zip(['-rp', '-rs'], params_list[1:]) for item in sublist]
if probabilities:
os.makedirs(prob_dir)
cmdline += ['-p', prob_path]
cmdline += [out_file]
else:
python_path = os.path.join(os.environ['HOME'], 'anaconda', 'envs', 'sitkpy', 'bin', 'python')
mod_path = os.path.join(os.environ['HOME'], 'CODE', 'mod_py')
nlwv_path = os.path.join(mod_path, 'pblf_py.py')
cmdline = [python_path, '-u', nlwv_path]
cmdline += ['--atlas_img_list'] + atlas_img_path_list
cmdline += ['--target_img', target_path]
cmdline += ['--atlas_lab_list'] + atlas_lab_path_list
cmdline += ['--method'] + params_list[:2]
cmdline += [item for sublist in zip(['--patch_radius', '--search_radius', '--fusion_radius', '--struct_sim', '--normalization',], params_list[2:]) for item in sublist]
if probabilities:
cmdline += ['--probabilities']
cmdline += ['--out_file', out_file]
# launch
qsub_launcher = Launcher(' '.join(cmdline))
qsub_launcher.name = "{}_joint".format(out_name)
qsub_launcher.folder = out_dir
# qsub_launcher.queue = 'short.q'
qsub_launcher.queue = 'default.q'
return qsub_launcher.run()
]
cmdline += [
os.path.join(in_dir, in_files_list[i]),
os.path.join(in2_dir, in2_files_list[i2])
]
if args.mask_file is not None:
cmdline += [
os.path.join(tmp_dir,
os.path.basename(args.mask_file[0]))
]
job_name = "{0}X{1}".format(RID_1 + '_' + sampleid_1,
RID_2 + '_' + sampleid_2)
qsub_launcher = Launcher(' '.join(cmdline))
qsub_launcher.name = job_name
qsub_launcher.folder = tmp_dir
qsub_launcher.queue = "short.q"
job_id = qsub_launcher.run()
if is_hpc:
wait_jobs += [job_id]
n_jobs += 1
list_of_jobs.append((job_name, i, i2))
# Wait for the jobs to finish (in cluster)
if is_hpc and n_total_jobs <= n_jobs:
print("Waiting for registration jobs to finish...")
call(wait_jobs)
n_jobs = 0
wait_jobs = [
args.reg_dir[0], file_name + args.in_deform_intfix[0] +
'1InverseWarp.nii.gz')
]
cmdline += [
'--output',
os.path.join(args.out_dir[0],
file.split('.nii.gz')[0] + args.out_suffix[0])
]
#
# launch
print "Launching warping of file {}".format(file)
qsub_launcher = Launcher(' '.join(cmdline))
qsub_launcher.name = file.split('.nii.gz')[0]
qsub_launcher.folder = args.out_dir[0]
qsub_launcher.queue = 'short.q'
job_id = qsub_launcher.run()
if is_hpc:
wait_jobs += [job_id]
# Wait for the jobs to finish (in cluster)
if is_hpc:
print "Waiting for warping jobs to finish..."
call(wait_jobs)
print "Warping finished."
out_path = img_file.replace(in_dir, args.out_dir[0])
if not os.path.exists(os.path.dirname(out_path)):
os.makedirs(os.path.dirname(out_path))
cmdline = [n4_path, '--image-dimensionality', '3']
cmdline += ['--input-image', img_file]
cmdline += ['--shrink-factor', '3']
cmdline += ['--convergence', '50x50x30x20', '1e-6']
cmdline += ['--bspline-fitting', '300']
cmdline += ['--output', out_path]
print("Launching N4 for {}".format(img_file))
qsub_launcher = Launcher(' '.join(cmdline))
qsub_launcher.name = os.path.splitext(os.path.basename(img_file))[0]
qsub_launcher.folder = os.path.dirname(out_path)
qsub_launcher.queue = 'short'
job_id = qsub_launcher.run()
njobs = njobs + 1
if is_hpc:
wait_jobs += [job_id]
if is_hpc and njobs >= n_total_jobs:
print("Limit found. Wait for jobs to finish...")
call(wait_jobs)
njobs = 0
wait_jobs = [
os.path.join(os.environ['ANTSSCRIPTS'], "waitForSlurmJobs.pl"),
'0', '10'
]